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Non-small Cell Lung Cancer Brain Metastasis Atlas [single nuclei RNAseq]

GSE223499 Homo sapiens (human) Single-nucleus RNA-seq 42 samples Submitted 2025/01/17 Platform GPL20301
At a glance

Single-nucleus RNA-seq · human · 42 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
42 samples: 31 × NSCLC_BM vs 11 × NSCLC_PTGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Single-cell and spatial genomic landscape of non-small cell lung cancer brain metastasesNature medicine · 2025
Summary (written by the submitters)
We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naïve non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naïve NSCLC brain metastases (BMs) . In total, we recovered 277,206 cell transcriptomes in 43 samples.
Published in
Single-cell and spatial genomic landscape of non-small cell lung cancer brain metastases
Tagore S, Caprio L, Amin AD et al. · Nature medicine 2025 · PMID 40016452 · doi:10.1038/s41591-025-03530-z
This dataset
Open GSE223499 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE223499_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA926595. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40016452) ↗
Study design
31 × NSCLC_BM vs 11 × NSCLC_PT

Supports a between-group comparison across 42 samples.

How we read this: 2 replicated groups read from 42 sample titles; they account for 42 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.